ANALYSIS OF VARIABLES INVOLVE IN RHEUMATOID ARTHRITIS DIAGNOSIS USING LOGISTIC REGRESSION

Rheumatoid Arthritis (RA) is a auto-immune disease in which body mistakenly considers some parts of its own system as pathogens and attacks them. RA is a chronic systemic inflammatory illness with prevalence of approximately 0.75% in India. It leads to irreversible joint damage and systemic complications. It is associated with substantial morbidity and increased mortality Better understanding of its pathophysiology has led to the progress of besieged therapies that have significantly enhanced outcomes. The key to beneficial achievement lies in identifying those who will have rigorous critical disease as early as possible, so that efficient management can be initiated prior to unalterable injure occurs. The primary aim of this study is to find out what factors play a significant role in determine the disease. From the brief account of discussion on observation and results of multivariate techniques are established, such techniques are important for they make it possible to encompass all the data from an investigation in one analysis. They in fact result in a clearer and better account of the research effort than do the piecemeal analyses of portions of data. Anti-cyclic citrullinated peptide (anti-CCP) antibody testing is mostly useful in the diagnosis of rheumatoid arthritis, with high specificity, presence early in the disease process, and ability to identify patients who are likely to have severe disease and unalterable injure. As of this observation concluded that disease also affects the quality of life i.e. disablement enhances.